Using RHINO Data to Monitor Emergency

Department Visits for Sexual Violence

Amanda Dylina Morse, MPH

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Agenda

Updates

o New facilities

o Data coverage

o Other updates

Monitoring emergency department visits for sexual violence

ESSENCE refresher using influenza-like illness

Questions

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New Facilities

Valley Medical Center

MultiCare

o Allenmore

o Covington

o Mary Bridge

o Deaconess North Emergency Department

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Percentage of Emergency Departments Available in NSSP ESSENCE (by County)

*Douglas, Skamania, and Wahkiakum Counties do not have emergency departments

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Other Updates of Note

RHINO is working with partners at DOH to produce automated reports of emergency department visits for opioid overdoses

o The project is still in its early stages, but we should have more to share in the near future

Kacey Potis will be staying with RHINO as a surveillance and validation epidemiologist focusing on our opioid surveillance work

RHINO has two graduate students from the COPHP program at UW helping us with a qualitative analysis project

o Ayla Ervin will be focusing on firearm injuries

o Tovah King will be focusing on motor vehicle collision injuries

RHINO staff will be out of the office the last week of January while we attend ISDS

o If you have urgent needs, Kacey will be available and you can contact her directly or via the Syndromic Mailbox

Conducting Surveillance

SEXUAL VIOLENCE

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Sexual Violence – Background

Risk for experiencing sexual violence is highest for trans and non-binary people, women,

and individuals between 12-34 years1

Not all sexual violence is reported to law enforcement—of 1,000 rapes

o 310 will be reported to the police2

o 57 reports will lead to an arrest2

o 6 rapists will be incarcerated2

There are many reasons a person may choose not to report and all of them are valid

o Fear of retaliation

o Expectation law enforcement cannot or will not help

o Shame from social stigmatization

Even if an individual does not want to report their assault, they may want or need to seek medical care

o Using syndromic surveillance data provides a way to better understand sexual violence without burdening patients or healthcare providers

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Challenges to Using Syndromic Data

Original chief complaint may not be the true reason for the patient’s visit

o Patient flow practices may have the original chief complaint gathered in a more public space

where the patient does not feel comfortable disclosing

Difficult to identify trans and non-binary patients

o Washington now has option to send “X” in lieu of M or F

Triage notes contain rich context about patient experiences, but may also have highly

identifiable information

o Patient names

o Patient street addresses and phone numbers

ICD-10 codes are used less consistently than for communicable diseases and may be indicating

a history of sexual assault rather than being treated for one at that visit

o Particularly common in obstetric and antenatal visits

o Z56.81 Sexual harassment on the job

o Z62.810 Personal history of physical and sexual abuse in childhood

o Z91.410 Personal history of adult physical and sexual abuse

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Sexual Violence

Time frame

o January – December 2018

Data source

o Facility location (full details)

Facility types

o Emergency care

o Inpatient practice setting

Fields included

o Chief complaint history

o Discharge diagnosis

Triage notes particularly valuable for validating the query

Submitted for index as Sexual Violence v3

o v1 and v2 available in NSSP ESSENCE

Query Composition

Chief Complaint Terms ICD-10 Codes

Included Excluded Included Excluded

Sexual assault Grape T74.2

Sexual assualt Scrape T76.2

Sexual abuse Z56.81

Rape Z62.810

Forensic nurse

exam Z04.41

Sane exam

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Results – Weekly Percentage of Visits (All Ages)

2,715 emergency department visits

identified*

o 0.16% of all emergency department

visits

o 0.11%-0.21% of weekly emergency

department visits

Several periods with elevated visits

throughout the year

o Late February (Midwinter Break)

o Memorial Day

o Last week of July

o Late September (Beginning of Autumn

Term)

o Halloween

* Facility counts changed over data period

Visit Increase (General)

Visit Increase (Academic Calendar)

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Results – Weekly Percentage of Visits (12-28 Years)

1,234 emergency department visits identified*

o 0.37% of all emergency department visits

o 0.21%-0.60% of weekly emergency

department visits

Some peaks match general population

o Memorial Day

o Last week of July

o Halloween

Additional (smaller) peaks at some points in

the academic calendar

o Beginning of Winter Term (Week 2)

o Mid-Winter Break (Week 9)

o Spring Break (Week 14)

o Start of Autumn Term (Week 39-40)

o End of Autumn Term (Week 49)

* Facility counts changed over data period

Visit Increase (General)

Visit Increase (Academic Calendar)

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Results – Triage Notes (2017-2018)

Triage notes were present for 68.69% of visits

o Although an optional data element, Washington strongly encourages facilities

to submit triage notes

Triage note content varies widely between facilities

o Some only bed number and patient chief

complaint

o Others full social determinants of health

Identifying information present for many visits

o Special care for protecting patient data

Many visits contain information about substance use

o Predominantly stimulants and alcohol

Contextual Information in Triage Notes

Presence in

Triage Notes

Time of assault 42.57%

Place of assault 21.43%

Identity of person doing harm 19.71%

“Jail health” or intake 6.57%

Mental health crisis 6.00%

Patient suspects was drugged 3.43%

Homelessness or insufficient housing 3.14%

Power relationship between assailant and

patient 2.86%

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Results – Sex and Age Group

Female patients over-represented across all age

groups

o 88.14% of all visits

o Female patients aged 18-44 years were 52.23%

of visits – more than double usual

representation

Age distribution was consistent with other sources

of sexual violence data regarding years of

highest risk

o Majority of patients were 18-44 years (58.53%)

or 05-17 years (20.55%)

o Smaller numbers of visits very young (under 5

years) and older (45+ years) patients

* Facility counts changed over data period

Patient Age

Group

Sexual Violence Visits All Visits

Female Male Female Male

00-04 6.85% 1.99% 2.57% 3.09%

05-17 18.01% 2.54% 4.16% 4.08%

18-44 52.23% 6.30% 21.54% 16.34%

45+ 9.24% 0.81% 12.36% 12.27%

Total 88.14% 11.86% 53.48% 46.51%

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Results – Sex and Age Group

Among female patients, rate per 10,000 visits for

sexual violence more than five times rate among

male patients

o Rate is higher across age groups

Rate per 10,000 visits highest among patients 05-

17 years

o Higher than anticipated based on percentage

of total visits

Rate per 10,000 Visits

Patient Age Group Female Male Overall

00 - 04 43.65 10.52 54.17

05 -17 70.92 10.21 81.13

18 - 44 39.71 6.31 46.02

45+ 7.16 0.73 7.89

Overall 26.99 4.17 43.48

* Facility counts changed over data period

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Results – Race and Ethnicity

Female patients were over-represented across

all racial and ethnic groups

Sexual violence disproportionately affects

some communities

o AIAN and Black or African American

patients seen at higher rate than other

racial groups

■ Consistent with data from Urban Indian Health

Institute 94% of AIAN women in Seattle area

experience sexual violence4

White and Native Hawaiian or Other Pacific

Islander patients had lowest rates of visits for

sexual violence

Fewer than 10% of visits did not report race or

ethnicity

Patient Demographic Rate per 10,000 Visits

Patient Race

American Indian or Alaska Native (AIAN) 27.52

Asian 17.53

Black or African American 23.32

Native Hawaiian or Other Pacific Islander 13.75

Not Reported 18.82

Other Race 18.64

White 15.41

Patient Ethnicity

Hispanic or Latinx 18.87

Not Hispanic or Latinx 16.21

Not Reported 13.66

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Results – Patient Location

19.91

10.52 17.03

10.85

19.21

11.27

18.32 11.84

County GroupingRate per

10,000 Visits

Clallam, Grays Harbor, Jefferson,

Kitsap, Mason, 10.85

Island, San Juan, Skagit, Snohomish,

Whatcom 19.91

King, Lewis, Pierce, Thurston 19.21

Clark, Cowlitz, Pacific, Skamania,

Wahkiakum 11.27

Chelan, Douglas, Okanogan 10.52

Grant, Kittitas, Klickitat, Yakima 18.32

Ferry, Lincoln, Pend Oreille, Spokane,

Stevens 17.03

Adams, Asotin, Benton, Columbia,

Franklin, Garfield, Walla Walla,

Whitman 11.84

Average Home to Facility

Distance (in Miles)

29.69

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What’s Next?

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Making Data Actionable

Syndromic data are most useful when they are actionable

o What do we do when we find something?

Cross-discipline partnerships are key to translating syndromic data into health promotion

o Your organization’s injury and violence staff are best placed to connect your data with community partners who can use it

Possible applications for sexual violence data

o Inform conversations with academic institutions about campus and teen dating violence

o Identifying recurring events coinciding with increased visit volume

o Monitor trends in communities where consent curricula are taught

o Designing more effective communication campaigns

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References

1. Victims of Sexual Violence: Statistics. RAINN | The nation's largest anti-sexual violence organization. https://www.rainn.org/statistics/victims-sexual-violence. Accessed October 9, 2018.

2. The Criminal Justice System: Statistics. RAINN | The nation's largest anti-sexual violence organization. https://www.rainn.org/statistics/criminal-justice-system. Accessed October 9, 2018.

3. US Census Quick Facts: Washington. United States Census Bureau. https://www.census.gov/quickfacts/wa. Accessed October 9, 2018

4. Our Bodies, Our Stories: Sexual Violence Among Native Women in Seattle, WA. Urban Indian Health Institute. http://www.uihi.org/wp-content/uploads/2018/08/UIHI_sexual-violence_r601_pagesFINAL.pdf. Accessed October 9, 2018.

Conducting Surveillance

INFLUENZA-LIKE ILLNESS

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ILI Surveillance – Data Source

Always begin by selecting your Datasource. For ILI surveillance, we typically use Facility Location (full details)

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ILI Surveillance – Time Resolution

Consider your time resolution. You may choose daily, weekly, monthly, quarterly, and yearly outputs

For ILI, weekly visits is the most common resolution choice.

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ILI Surveillance – As Percent Query

ILI is conventionally monitored looking at visits for ILI as a percentage of total visits.

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ILI Surveillance – Start and End Points

Influenza season is generally CDC Week 40 to CDC Week 20

By setting your time frame back to a previous year, you can compare flu seasons

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ILI Surveillance – Available Query Fields

The available query fields box shows a list of available parameters you may choose for your query

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ILI Surveillance – CC and DD Category

The CC and DD Category field contains a variety of user-created queries indexed in ESSENCE which typically search multiple data fields simultaneously

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ILI Surveillance – Facility Type and Patient Class

While building your theory, it is also important to consider the facility types and patient classes relevant for your inquiry

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ILI Surveillance – Explain Query

If you would like to view a depiction of your query’s numerator and denominator, click the Explain Qry button

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ILI Surveillance – Facility Type and Patient Class

When your query is complete, click Time Series

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ILI Surveillance – Time Series Graph

You have a graph! It looks pretty great!

Now let’s compare this respiratory season to last year

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ILI Surveillance – Data Series Options

Start by opening up the “Data Series Options” drop down

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ILI Surveillance – Selecting Your Stratifications

Select “Year” from the bottom of the “Within Graph Stratification” dropdown

Select 30 (or your week of choice) from the “Graph Start Week” dropdown

Click update

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ILI Surveillance – Year-Over-Year Stratification

Edit your title and axes using the “Graph Options” button

Download your graph using the “Download” button (I don’t recommend choosing to zoom in)

Contact us!

RHINO@DOH.WA.GOV